---
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# convnext-tiny-224-finetuned

This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2328
- Logloss: 1.2328
- Accuracy: {'accuracy': 0.5220588235294118}

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Logloss | Accuracy                          |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:---------------------------------:|
| No log        | 0.9412  | 8    | 1.6104          | 1.6104  | {'accuracy': 0.2426470588235294}  |
| 1.6172        | 2.0     | 17   | 1.5560          | 1.5560  | {'accuracy': 0.2867647058823529}  |
| 1.5532        | 2.9412  | 25   | 1.5107          | 1.5107  | {'accuracy': 0.36764705882352944} |
| 1.4806        | 4.0     | 34   | 1.4612          | 1.4612  | {'accuracy': 0.40441176470588236} |
| 1.4041        | 4.9412  | 42   | 1.4208          | 1.4208  | {'accuracy': 0.43014705882352944} |
| 1.3407        | 6.0     | 51   | 1.3774          | 1.3774  | {'accuracy': 0.4632352941176471}  |
| 1.3407        | 6.9412  | 59   | 1.3422          | 1.3422  | {'accuracy': 0.45588235294117646} |
| 1.2852        | 8.0     | 68   | 1.3110          | 1.3110  | {'accuracy': 0.47058823529411764} |
| 1.2272        | 8.9412  | 76   | 1.2849          | 1.2849  | {'accuracy': 0.49264705882352944} |
| 1.1841        | 10.0    | 85   | 1.2634          | 1.2634  | {'accuracy': 0.5073529411764706}  |
| 1.1625        | 10.9412 | 93   | 1.2540          | 1.2540  | {'accuracy': 0.49264705882352944} |
| 1.1166        | 12.0    | 102  | 1.2423          | 1.2423  | {'accuracy': 0.5147058823529411}  |
| 1.1079        | 12.9412 | 110  | 1.2351          | 1.2351  | {'accuracy': 0.5257352941176471}  |
| 1.1079        | 14.0    | 119  | 1.2328          | 1.2328  | {'accuracy': 0.5220588235294118}  |
| 1.0974        | 14.1176 | 120  | 1.2328          | 1.2328  | {'accuracy': 0.5220588235294118}  |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1